<p>Summary of Linear Mixed-Effects Random Intercept Models Examining Gait Parameters and T

This dataset contains linear mixed-effects random intercept models examining gait parameters (e.g., stride length, cadence) and their interactions with visit number and mean tug duration. The data supports longitudinal gait analysis in biomechanics research.

Use Cases

• Analyze gait parameter trends across visits using random intercept models.
• Assess tug duration effects on gait variability.
• Compare interaction effects between visit and tug duration across gait metrics.

Strengths

• Longitudinal design with multiple visits per subject.
• Mixed-effects models account for within-subject correlation.
• Focus on tug duration interaction provides clinical relevance.

Limitations

• Sample size unknown; may limit generalizability.
• Specific gait parameters not listed in description.
• Data freshness unknown; collection period unspecified.

Provenance

Source

Data origin is figshare; authoritative but details limited.

Collection Method

Collection method not described in provided metadata.

Time Range

Temporal coverage not specified.

Geography

Geographic coverage not specified.